The answer is to change DISTSTYLE from ALL to KEY on a column used in frequent joins. This is correct because DISTSTYLE ALL copies the entire large fact table to every node, wasting storage and creating network bottlenecks during both data loading and query execution, whereas DISTSTYLE KEY collocates related rows from the fact and dimension tables on the same slice based on the join key, eliminating the need for costly data redistribution or broadcasting across the network. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of Redshift distribution key optimization and how table design directly impacts query performance—a common trap is assuming ALL style is always faster for joins, but it backfires on large tables due to excessive data movement. Remember the memory tip: “ALL is small, KEY is for joins”—use ALL only for tiny dimension tables, and always choose a high-cardinality join column as your distribution key for large fact tables.
DEA-C01 Data Store Management Practice Question
This DEA-C01 practice question tests your understanding of data store management. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data engineering team uses Amazon Redshift for analytics. They notice that queries on a large fact table are slow. The table is distributed using DISTSTYLE ALL. Which design change would most likely improve query performance?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Change DISTSTYLE to KEY on a column used in frequent joins.
DISTSTYLE ALL copies the entire table to every node, which is inefficient for large fact tables because it wastes storage and network bandwidth during data loading and query execution. Changing to DISTSTYLE KEY on a column used in frequent joins collocates related rows on the same slice, reducing the need to broadcast or redistribute data across the network during joins, which directly improves query performance.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Change DISTSTYLE to EVEN to distribute rows evenly across slices.
Why it's wrong here
EVEN distribution can cause broadcast joins and degrade performance.
✗
Increase the number of nodes in the Redshift cluster.
Why it's wrong here
Adding nodes is a scaling solution but does not fix the distribution design issue.
✗
Change the table to use a SORTKEY on the most frequently filtered column.
Why it's wrong here
SORTKEY improves range scans but does not address distribution overhead.
✓
Change DISTSTYLE to KEY on a column used in frequent joins.
Why this is correct
KEY distribution collocates rows on the same node, reducing data movement during joins.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume adding a SORTKEY (Option C) is the universal performance fix, but for large fact tables the dominant bottleneck is data distribution and join collocation, not scan efficiency.
Detailed technical explanation
How to think about this question
Under the hood, Redshift uses a massively parallel processing (MPP) architecture where data is distributed across slices (each slice is a CPU core and its dedicated storage). When DISTSTYLE ALL is used, the entire table is replicated to every slice, meaning any join with another table forces a broadcast of the other table or a redistribution of the fact table, consuming significant network bandwidth and memory. Changing to DISTSTYLE KEY on a join column ensures that rows with the same key value land on the same slice, allowing Redshift to perform a collocated join without moving data between slices, which is critical for large fact tables in star schema designs.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Change DISTSTYLE to KEY on a column used in frequent joins. — DISTSTYLE ALL copies the entire table to every node, which is inefficient for large fact tables because it wastes storage and network bandwidth during data loading and query execution. Changing to DISTSTYLE KEY on a column used in frequent joins collocates related rows on the same slice, reducing the need to broadcast or redistribute data across the network during joins, which directly improves query performance.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company uses Amazon Redshift for analytics. The data engineer notices that some queries are slow and the EXPLAIN plan shows a 'Seq Scan' on a large table. Which data store management action would most likely improve query performance?
medium
A.Run the ANALYZE command to update table statistics.
B.Enable automatic compression on the table.
✓ C.Define appropriate sort keys and distribution styles.
D.Run the VACUUM command to reclaim space.
Why C: Option D is correct because using sort keys and distribution styles can significantly improve query performance by reducing scans and data shuffling. Option A is incorrect because VACUUM reclaims space but does not directly improve scan performance. Option B is incorrect because ANALYZE updates statistics but does not change the physical layout. Option C is incorrect because compression is for storage, not query speed.
Variation 2. A company uses Amazon Redshift for analytics. The data engineer notices that queries are slow and the system is experiencing high disk usage. The engineer suspects that the distribution style is suboptimal. Which action should the engineer take to improve query performance?
hard
A.Convert all tables to use SORTKEY on the most frequently filtered column.
B.Increase the number of nodes in the cluster to distribute data across more slices.
✓ C.Use the DISTSTYLE AUTO setting and analyze query patterns to let Redshift choose.
D.Set all tables to DISTSTYLE EVEN to distribute data evenly.
Why C: Option B is correct because analyzing query patterns helps choose optimal distribution. Option A changes all tables, which may not be ideal. Option C is for storage, not distribution. Option D is for sort keys.
Variation 3. A company uses Amazon Redshift for analytics. The data engineering team wants to improve query performance for frequently used aggregate queries. Which TWO actions would help achieve this?
medium
A.Increase the number of WLM query queues
✓ B.Use distribution keys to collocate data on the same node slices
C.Run the VACUUM command to reclaim space from deleted rows
✓ D.Define appropriate sort keys on the tables
E.Increase the number of nodes in the cluster
Why B: Distribution keys determine how data is distributed across node slices in Amazon Redshift. By choosing distribution keys that align with the join and aggregation columns, the database can collocate related data on the same slice, minimizing data movement during query execution. This directly improves performance for aggregate queries by reducing network traffic and enabling local computation.
Variation 4. A company uses Amazon Redshift for analytics. They notice that some queries are slow due to data redistribution. The data engineer wants to minimize data movement across nodes. Which table design strategy should be used? (Choose TWO.)
hard
A.Set the distribution style to AUTO for all tables.
B.Define compound sort keys on frequently filtered columns.
✓ C.Choose a distribution key that matches the join key for large tables.
D.Use EVEN distribution for all tables.
✓ E.Use distribution style ALL for small dimension tables.
Why C: Option C is correct because when large tables are joined on their distribution keys, Redshift can perform a collocated join, meaning the matching rows are already on the same node slice, eliminating the need to redistribute data across the network. This directly minimizes data movement and speeds up query execution.
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